Fuel Spray Simulation of High-Pressure Swirl-Injector for DISI Engines and Comparison with Laser Diagnostic Measurements

11 Pages·0.756 MB·English

by  Chryssakis Ch.A., Assanis D.N.

2003-01-0007
Fuel Spray Simulation of High-Pressure Swirl-Injector
for DISI Engines and Comparison with
Laser Diagnostic Measurements
Christos A. Chryssakis, Dennis N. Assanis
University of Michigan
Jee-Kuen Lee, Keiya Nishida
University of Hiroshima
Copyright © 2003 Society of Automotive Engineers, Inc.
ABSTRACT investigation, the High-Pressure Swirl (HPS) injectors are
the most commonly used in commercial applications
A comprehensive model for sprays emerging from high- today.
pressure swirl injectors in DISI engines has been
developed accounting for both primary and secondary HPS injectors operate at relatively high pressures (4-12
atomization. The model considers the transient behavior MPa) and their design enhances atomization as well as
of the pre-spray and the steady-state behavior of the turbulence levels in the combustion chamber for a more
main spray. The pre-spray modeling is based on an efficient combustion process. Instead of the round jet
empirical solid cone approach with varying cone angle. solid-cone structure common to diesel injectors, the HPS
The main spray modeling is based on the Liquid injector produces a hollow-cone spray structure by
Instability Sheet Atomization (LISA) approach, which is providing a swirl rotational motion to the fuel inside the
extended here to include the effects of swirl. Mie injector. The key advantage of hollow cone sprays is the
Scattering, LIF, PIV and Laser Droplet Size Analyzer high area to volume ratio, which can lead to the required
techniques have been used to produce a set of level of atomization without large penetration lengths.
experimental data for model validation. Both qualitative
comparisons of the evolution of the spray structure, as The development of the spray emerging from an HPS
well as quantitative comparisons of spray tip penetration injector can be divided into two phases: the transient
and droplet sizes have been made. It is concluded that phase at the beginning of injection and the steady-state
the model compares favorably with data under phase that corresponds to the largest part of the injection
atmospheric conditions. However, discrepancies occur process. Upon the start of injection, due to the lack of
under higher ambient pressures, suggesting that the high swirl, a solid-cone-like structure appears with narrow
physics of the breakup mechanism should be further cone angle and relatively large droplets. As the fuel
investigated for these conditions. velocity inside the nozzle increases, the angular
momentum and the centrifugal forces increase too, thus
INTRODUCTION forcing the fuel to form a hollow-cylinder structure,
adjacent to the walls of the nozzle. This structure is
The design of more powerful, fuel-efficient, and transformed into a hollow-cone as the fuel emerges in the
environmentally friendly gasoline engines is currently one combustion chamber. It has been found experimentally
of the main goals of engine researchers and that the higher the swirl intensity of the emerging fuel, the
manufacturers worldwide. In this context, the Direct- larger the cone angle of the resulting spray [2,7,8]. The
Injection Spark-Ignition (DISI) engine promises hollow-cone formed is a liquid sheet that penetrates in the
significant advantages, especially in improving fuel high-pressure environment of the cylinder until it
economy and reducing CO emissions [1-8]. However, disintegrates into circular ligaments that further break up
2
there are challenges associated with the very short into droplets.
amount of time available for the fuel spray to atomize and
form an adequate mixture for satisfactory combustion. A literature review of the most significant approaches
Consequently, suitable fuel injectors are needed to towards modeling the liquid sheet shows that the first
provide sufficient control on the spray motion and meet promising attempt to model a hollow-cone spray has been
the basic requirements for atomization and mixing. published in 1995 by Dorfner et al. [9]. In 1997, an
Among the various injectors that have been under improved model has been presented by Han et al. [10],
and in 1999, the Linearized Instability Sheet Atomization role both in fuel consumption and pollutant formation. The
(LISA) approach by Schmidt et al. [11, 12] appeared in fuel behavior and spray formation process after the start
the literature. All three models estimate the basic of injection depends on the injector characteristics,
characteristics of the liquid fuel sheet formed in the operation and the physics of the flow. A typical internal
vicinity of the injector and utilize these estimates for the geometry of a swirl injector is shown in Figure 1. As
prediction of spray features, such as the size of the injection starts, some amount of fuel that had been
resulting droplets, their velocity and the location where trapped in the tangential slots from the previous injection
they first appear. A comparison of the predictions from all event flows out lacking strong swirl, since it does not go
three models over a large pressure range shows relatively through the entire length of the tangential slots. In
small differences between them. This is expected since addition, at the beginning of injection the velocity has not
the models have all been calibrated to give reasonable reached its maximum value, thus contributing to the low
predictions for swirl sprays [13]. However, while they all swirl condition. As injection proceeds, the fuel flows
include a number of empirical equations, the LISA through the tangential slots into the nozzle and forms a
approach is more physical and less dependent on liquid film on the nozzle walls. The film later transforms
empirical constants (only 2, as opposed to 5 for Han et. al into a rotating hollow-cone structure, as the fuel emerges
and 8 for Dorfner et al.) Furthermore, the LISA model from the injector. The geometrical characteristics of the
provides an estimate for the initial droplet size and takes slots (round or rectangular exit, angle) determine the swirl
into account the effect of ambient pressure, by including intensity of the spray. The fuel needs to have sufficiently
the fuel/ambient gas density ratio in the calculation. high angular velocity in order to form the liquid film on the
Nevertheless, a need still exists for modeling pre-spray wall; otherwise it flows out of the nozzle with its axial
effects and for accounting for the effects of swirl on the component of velocity, without performing any swirl
liquid sheet atomization. motion, in the form of a blob.
The objective of this work is to develop a more Understanding and modeling the phenomena taking place
comprehensive model for sprays emerging from HPS inside the nozzle is a challenging task due to the fact that
injectors in DISI engines that accounts for both primary the internal geometry has to be known. In the past, zero-
and secondary atomization. The model considers the and one-dimensional models have been developed,
transient behavior of the pre-spray and the steady-state providing simplified solutions to the problem [15, 16]. The
behavior of the main spray. The pre-spray modeling is main assumption of these models is that steady-state has
based on an empirical solid cone approach with varying been achieved and a single-phase approach is followed.
cone angle. The main spray modeling is based on the These models can provide estimates for the injection
LISA approach, which is extended here to include the velocity and the initial conditions for the steady-state part
effects of swirl. A first attempt to validate the proposed of injection, but cannot be used to predict injection start-
model against experimental data obtained with PIV and up.
LIF techniques has been presented in [14]. In the
current work, additional experimental data taken for a
different injector, including spray tomograms and air
velocity patterns, are used for model validation.
The paper is arranged as follows. First, the challenges of
modeling the internal flow in the nozzle are briefly
summarized, followed by an empirical approach for
modeling the pre-spray. Subsequently, the extensions
incorporated in the LISA model, used to simulate steady-
state liquid sheet formation and breakup, are presented.
Next, the experimental setup used for qualitative and
quantitative comparisons of spray images, droplet sizes
and tip penetrations are described. Finally, comparisons
between KIVA-3V predictions and measurements of HPS

sprays are made and appropriate conclusions are drawn.
Figure 1: Details of injector nozzle.
PRE-SPRAY MODELING
More sophisticated approaches have appeared in the last
Experimental studies of hollow-cone sprays with optical
few years, including detailed 2-D and 3-D multi-phase
engines and static cells have illustrated that the hollow
flow CFD simulations of the flow [17, 18]. Such models
cone structure does not appear immediately after the start
can provide precious insight on the phenomena taking
of the injection process. A short period of time elapses
place during the start-up phase of injection, and can also
before the liquid sheet is formed and the physical
predict when transition between the pre-swirl and the
processes taking place during this time play a significant
main spray takes place. However, CFD models are
computationally expensive and, in addition, the detailed U =Ucosq and U =Usinq (4)
xo qo
nozzle geometry has to be provided as input.
respectively, at the exit of the injector hole.
In order to overcome problems associated with a detailed
CFD analysis, a simplified solution has been adopted Wave oscillations on the liquid sheet cause its break-up
here. First, a solid-cone-like injection is performed, into ligaments and finally droplets. The break-up length,
representing the pre-spray, and the cone angle is L, and break-up time, t , are estimated using the
gradually being increased, using a linear profile. After equations derived in the original LISA model:
some point, defined by the user in the input file, the code
switches into a hollow-cone structure, while the cone (cid:230) h (cid:246)
angle is still increasing until the steady-state value is L=Ut =U ln(cid:231) b (cid:247) , (5)
reached. In addition, a new velocity profile has been W (cid:231)Ł ho (cid:247)ł
added to KIVA, allowing for gradually increasing injection
velocity during the start-up injection period. A similar
where ln(h /h )=12 and W is the maximum wave growth
b o
process with much shorter duration can be used at the
rate. The mean droplet diameter, d , is given as
end of injection by decreasing the cone angle and D
velocity to take into account fuel dripping.
1/3
(cid:230) 2 (cid:246)
MAIN SPRAY MODELING d =(cid:231)(cid:231) 3pdL (cid:247)(cid:247) , (6)
D (cid:231) K (cid:247)
LIQUID SHEET FORMATION AND PRIMARY BREAKUP Ł L ł
The primary breakup approach adopted here is based on where d is the ligament diameter estimated from the
L
the Linearized Instability Sheet Atomization (LISA) model sheet thickness at the break-up location and K is a wave
L
[11, 12], with appropriate extensions. According to the number, according to the LISA model.
original model, the thickness of the liquid film, h , formed
o
at the nozzle exit, is calculated from continuity, DROPLET SIZE DISTRIBUTION
( )
m& =pr uh d - h (1) The computed mean diameter from the LISA model is
l l o o o
assumed to represent the SMD of the droplet parcels
introduced at the liquid sheet break-up length. In order to
where m& is the fuel mass flowrate, d the nozzle
l o properly compute evaporation and combustion, the details
diameter, r the fuel density and u the axial component of the size distribution of droplets are important. While the
l
standard c2-distribution is used in KIVA, the Rosin-
of the velocity at the nozzle exit, calculated from:
Rammler cumulative distribution better suits the droplet
size distribution measured in swirl injectors [10],
u = U(cid:215)cosq, (2)
Accordingly, the volume distribution V is given by
where q is the half spray angle and U is the relative fuel-
Ø qø
air velocity, assumed to be equal to the liquid velocity V =1- expŒ - (cid:231)(cid:230) D(cid:247)(cid:246) œ , (7)
since the air is considered to be initially quiescent, and Œ Ł D ł œ
º ß
calculated as in Han, et al. [10],
2D P leading to:
U =K l . (3)
v rl dV = qDq- 1expί - (cid:231)(cid:230) D(cid:247)(cid:246) qϿ . (8)
dD q Œ Ł D ł œ
D º ß
where K is the discharge coefficient of the nozzle and
v
D P the pressure difference between the rail and the
l
where D is the size of the individual droplets. The
ambient pressure.
distribution parameter, q, is set to 3.5, according to the
work of Han et al., [10], and
In this work, Eq. (3) is being retained and used only in
cases where the injection velocity profile is not being
measured experimentally. Instead of assuming that the D =d G (cid:231)(cid:230) 1- q- 1(cid:247)(cid:246) , (9)
D Ł ł
angular velocity of the spray is converted into a radial
component of velocity, as in the LISA model, the angular
where d is the droplet size diameter calculated from
velocity component is conserved and assigned to the D
equation (10) and is being used here to initialize the
injected particles. The axial and angular velocity
components of the liquid film are assumed to be:
droplet size distribution. G is the gamma function, given fine grid in the vicinity of the injector to catch the initial
by: position of the droplets.
¥ The proposed injection strategy of introducing the swirl
G (x)= (cid:242) e- ttx- 1dt. (10) concept does not affect the tip penetration or SMD
0 predictions but gives the flexibility to the user to control
the swirl intensity of the spray. It is expected that a
As shown in Figure 2, the c2-distribution yields larger difference will be apparent when ambient air vector plots
standard deviation and includes many large droplets, are compared at planes perpendicular to the injector axis,
while the Rosin-Rammler contains more droplets with very close to the nozzle (up to 10-15 mm downstream).
radius closer to the SMD value. This means that the c2- Farther away from the nozzle the swirl component seems
distribution could overestimate the tip penetration of the to fade out very quickly and only the radial component is
spray because larger droplets have larger momentum and dominant.
can move in a longer path than smaller ones before they
evaporate. In addition, larger droplets cannot be totally
evaporated in the short time interval before ignition starts.
2
Rosin-Rammler vs. c
0.08
chi-square j
0.06
n Rosin-Rammler
o
uti
b 0.04
ri
st
Di
e 0.02
m
u
ol Figure 3: Circle-Injection Strategy
V 0
SECONDARY DROPLET BREAKUP
-0.02
0 20 40 60 80 100
Droplet Radius [m m] The TAB (Taylor Analogy Breakup) breakup model has
been presented by Amsden and O’Rourke in 1987 [19]
and is still considered one of the standard models used
for spray breakup calculations. The model is based on an
Figure 2: Comparison of Rosin-Rammler and c2 size analogy, suggested by Taylor and improved by Amsden
distributions, SMD=30 m m. and O’Rourke, between an oscillating and distorting
droplet and a spring-mass system. The advantage of the
A further modification in the KIVA code was required in model over earlier approaches to the problem is the fact
order to implement the swirl motion of the spray. Instead that it predicts that there is not a unique critical Weber
of introducing parcels at a single point, the concept of number, but breakup of each droplet depends on the
circle-injection has been introduced; therefore, parcels history of its velocity relative to the gas.
are injected at a plane downstream from the injector,
corresponding to the break-up length of the liquid sheet, EXPERIMENTAL SETUP
as shown in Figure 3.
A complete set of data for spray model validation has
The angle j is the swirl-angle and has been included in been acquired at the Spray and Combustion Laboratory
the input file in order to offer the flexibility to the user to of the University of Hiroshima using Laser-Induced
deactivate this option. Throughout this work, a value of Fluorescence (LIF), Particle Image Velocimetry (PIV),
j =90o has been used to obtain the tangential velocity Mie Scattering, and Laser Droplet Size Analyzer (LDSA)
component. This injection strategy not only allows the techniques to characterize a High-Pressure Swirl
introduction of the tangential component of velocity, but Injector, provided by Mitsubishi Electric Company. The
also permits to inject the droplets at the point where the measurements have been obtained in an optical static
liquid film breaks up. This has the advantage that the cell, with size 10· 10· 10 cm. The experimental conditions
droplets are inserted at the point where they are are given in Table 1. The ambient gas is Nitrogen (N). A
2
generated and have the calculated size, avoiding any non-evaporating dry solvent is used as the fuel. The fuel
changes that could be imposed by the break-up, collision properties are compared to the properties of commercial
or evaporation models. Also, it does not require a very gasoline in Table 2.
Delay p
Pulse Injector for
Table 1: HPS Injector specifications and Generator Fuel Injection
experimental conditions. Accumulator
CCD Camera
PIVCAM 10-30
Number of Tangential Slots 6 TSI
HLiogwh -Pass
Injector Filter
Cone Angle [deg.] @ atm 50 Driver p
Injector for
p
Injection Pressure [MPa] 5 Tracer Injection
Laser Pulse
Injection Duration [ms] 1.25 Synchronizer
Injection Quantity [mg/inj.] 7.24 Computer Signal
Fuel Dual
Laser Pulse Nd:Yag
Ambient Temperature [K] 293 INSIGHTTM Tracer Nd:Yag Laser Laser
N
2
N
Ambient Pressure [MPa] 0.1, 0.4 Cylin2ders
Fluorescent dye for LIF Rhodamine B
imaging (C H NOCl)
28 31 2 3
Figure 4: Experimental setup for PIV measurements.

CCD camera (TSI PIVCAM 10-30, cross-correlation,
1000x1016 pixels, 8-bit gray level), with a 60 mm focal
Table 2: Comparison of Fuel Properties
length Nikon Micro Nikkor lens.
Property Gasoline Dry Solvent
In order to measure ambient air velocity, prior to fuel
Density [kg/m3] 745 770
spray injection, rhodamine B-water solution is injected
Kin. Viscosity into the ambient air by the swirl-type injector used to
2.25 1.032
[mm2/s] disperse fine fluorescent liquid particles as tracers for the
ambient air motion. When illumination is provided by the
Surface
2.25· 10-2 2.45· 10-2 thin laser sheet, the light scattered from the fuel droplets
Tension [N/m]
has the same wavelength as the Nd:YAG laser (532 nm),
Flash Point [K] 230 443 while the light scattered from the fluorescence tracers has
a slightly longer wavelength. An optical high-pass filter
(>560 nm), illustrated in Figure 5, is used to discriminate
between the scattered lights from spray droplets and
The experimental setup for the spray tomograms and PIV fluorescent tracers. As the rhodamine B absorbs the light
measurements is shown in Figure 4. The experimental of the laser and fluoresces the light whose wavelength is
setup is composed of a constant volume chamber, an larger than 570 nm, the fluorescence signals from the
injection system and a LIF-PIV system, used for spray tracers are transmitted through the high-pass filter to the
imaging and measuring the velocities of the fuel spray CCD camera.
droplets and the fluorescence tracers tracking the
ambient air motion. The constant volume chamber can be
pressurized up to 10 MPa with N gas, and has capability
2
of two-dimensional positioning. Two injectors, one used
MMiiee SSccaatttteerriinngg High--PPaassss FFiilltteerr
for injecting the fuel spray and the other for the
((553322nnmm)) ((>>556600nnmm))
SSpprraayy
fluorescence tracers, are installed at the upper and lower
parts of the constant volume chamber. The fuel is
supplied under constant pressure from an accumulator
NNdd::YYAAGG LLaasseerr
pressurized with N gas.
2 ((553322nnmm))
The LIF-PIV system is composed of a dual pulse,

Nd:YAG laser (LASERPULSE, wavelength of 532 nm, TTrraacceerr

MMiiee SSccaatttteerriinngg FFlluuoorreesscceennccee
power of 25 mJ), a CCD camera and a synchronizer
&& FFlluuoorreesscceennccee ((557700--662299nnmm))
system. For the purpose of obtaining spray tomograms,
the spray is illuminated by the thin (1 mm thick) laser
sheet and the images of the Mie-scattered light produced Figure 5: Principle of LIF-PIV technique
by the fuel droplets is captured by a high-resolution digital
In order to perform PIV measurements, the fuel droplets COMPARISON WITH EXPERIMENTS
and the fluorescence tracers are illuminated by the light
sheet twice, within a short time delay. The injection timing THE NUMERICAL MODEL
and duration of the fuel and the tracer injector are
controlled by a delay pulse generator (Stanford Research For the numerical simulations performed in this work
System, Model DG535). In addition, the triggering pulses KIVA-3V [20, 21] has been used with the modifications
of the dual Nd:YAG laser and CCD camera are produced described in the previous sections. The spray droplets
by a highly accurate synchronizer (LASERPULSE, Model are represented by 5,000 computational parcels, each
610032), which is externally triggered by the delay pulse one containing droplets with the same properties.
generator. This timing control procedure is shown in Isooctane (n-C H ) has been used as a fuel in the
8 18
Figure 6. computations, with properties slightly different than the
ones of the dry-solvent used in the experiments. The
collision model has been deactivated, as it has been
found to produce spray structures wider than normal. In
Injection Pulse for LIF Tracer
addition, since injection occurs in quiescent environment,
the relative velocities between droplets are very small and
collision phenomena are not expected to play a key role
Injection Pulse for Spray
in the spray development. However, collisions might be
important in simulations of real engine operation, as the
Synchronizer Trigger ambient flow field is much more likely to cause the
droplets to collide with each other.
CCD Camera Exposure Frame 1 Frame 2 The computational grid consists of a 3-D representation
of the optical static cell used in the experiments, with
dimensions 10· 10· 10 cm and homogeneous
Nd:Yag Laser Pulses

computational cells with size of 2.4 mm, which is typical
of the grids used in engine simulations. A grid sensitivity
Figure 6: Timing charts for LIF-PIV measurements.
analysis has been performed to investigate the effect of
the grid size on the predicted study. It has been found
.
that for cell sizes varying from 2.17-3.23 mm, there is no
significant effect on the computational results. The
The CCD camera records two consecutive single-
required CPU time has been found to increase linearly
exposure images, in the frame straddle exposure mode,
from 4 minutes for 30,000 cells to 17 minutes for 95,000
by using two laser light pulses. In this study, the
cells. In Figures 7a and 7b, a grid sensitivity analysis of
separation time between the two laser pulses is adjusted
predicted tip penetration and SMD shows very small
in the range of 5 - 20 µs and 50 - 100 µs, to get
difference between the various grid sizes. All the
reasonable fuel spray and fluorescent tracer images
calculations have been performed on a LINUX system,
suitable for velocity analysis. The images obtained are
which has been found to be approximately 5 times faster
transferred to a computer, and then 2-D velocity vectors
than a UNIX workstation.
of the fuel droplets and the fluorescence tracers are
obtained using a cross-correlation PIV measurement
technique, based on the cross-correlated sub-regions of
Tip Penetration
frame-straddle images.
5
The SMD of the spray is measured by using a Laser m] 4
Droplet Size Analyzer (LDSA) system (TOHNICHI c
Computer Co., Model 1400A), which is based on the n [ 3
o
laser diffraction, at the axial position of 27 and 35 mm at ati 2
ambient pressure of 0.1 and 0.4 MPa. A He-Ne laser etr Experiment
n 46656 cells
(wavelength of 632.8 nm, power of 1mW), which forms a e 1
p 68921 cells
beam of 8 mm diameter, is used as the light source. The p 97336 cells
receiving lens has a 300 mm focal length to collect the Ti 0
scattering light from the spray droplet.
-1
-0.2 0 0.2 0.4 0.6 0.8 1 1.2
TIme after SOI [msec]

Figure 7 a: Grid sensitivity analysis of tip penetration
predictions
At 0.2 ms after SOI, a very dense spray with small cone
SMD angle can be seen. At this early timing, the main spray
50 has not started forming yet. At 0.5 ms after SOI, the main
spray is fully developed and the pre-spray can be easily
40 46656 cells distinguished from the main spray. At 0.8 ms, both parts
68921 cells of the spray are still noticeable. An interesting observation
m] 30 97336 cells is that the distance between the pre- and the main spray
mD [ has now increased and that the size of the pre-spray has
M 20 decreased. Also, a recirculation region appears for the
S
first time close to the bottom of the main spray. This is
10 driven by the vortices that are illustrated clearly with the
aid of velocity plots, shown in Fig. 9. Overall, the
0 snapshots shown in the first row indicate reasonably good
0 0.0005 0.001 0.0015 0.002
predictions of both the pre-spray and the main spray
Time after SOI [sec]
features. In the second row, where the pre-spray has
moved farther away from the main spray, it appears that
Figure 7 b: Grid sensitivity analysis of SMD predictions the model can only predict correctly the main spray
structure. As will be discussed later, the TAB model used
GENERAL COMMENT for break-up of the pre-spray quickly produces droplets
of smaller size and thus limited penetration, compared to
Typical breakup lengths for liquid sheets are on the order reality. An additional problem for late timings is that there
of 1-2 mm downstream of the nozzle exit. In this region, is a lack of computational parcels to represent the entire
the spray is very dense and accurate experimental data formed structure.
cannot be acquired with conventional laser techniques.
While a promising time-resolved x-radiography method Figure 9 compares PIV-LIF measured and KIVA-3V
for visualizing and measuring dense sprays has been predicted ambient air vector plots at 0.8 ms, 1.3 ms and
recently developed at the Argonne National Laboratory 1.8 ms after the SOI. On the left hand side of the images,
[22, 23], data for validation of liquid sheet formation in the experimental results are shown and on the right hand
HPS injector sprays are not readily available. side the numerical ones, both within a domain of 75×40
Consequently, our spray model can only be validated mm. From a qualitative point of view, predictions are in
based on data collected far downstream (at least 20-25 very good agreement with measurements. In particular,
mm below the orifice). However, in these downstream the same vortex patters are observed, driving the
locations, other phenomena, such as secondary recirculation of spray droplets near the spray boundary.
atomization, evaporation, air entrainment and probably In addition, the predicted center of the vortex patterns
collisions between droplets take place and affect the appears to correlate well with velocity measurements for
spray shape and droplet sizes. Nevertheless, useful early instants. However, later on, it appears that the
conclusions can be extracted from qualitative predicted center of vortex activity trails behind the
comparisons of the development of the overall spray location of the observed one.
structure, as well as from quantitative comparison of
spray tip penetration and droplet sizes at such Comparison of absolute magnitudes indicates
downstream locations. discrepancies between measurements and computations.
These discrepancies can be partially explained by the
QUALITATIVE COMPARISON fact that in the vicinity of the spray boundary the
experimental measurements are not very accurate due to
A qualitative comparison of the observed and predicted the high density of fuel droplets that interfere with the
spray structure is presented in Figure 8, where five velocity tracers. Other possible causes are limitations in
different snapshots are shown at 0.2 ms, 0.5 ms, 0.8 ms the momentum coupling between the gas and liquid
(first row), and at 1.3 ms and 1.8 ms (second row) after phases in KIVA-3V, slip between the real gas and the
the Start Of Injection (SOI). The scale is given on the left tracer particles, and calibration errors.
of each row, with a 60· 30 mm and a 75· 40 mm domain
of the computational grid and the static cell illustrated for It is interesting to note that at 1.8 ms, the experimental
comparison of the experiments with the model for the first plots show a high density of high velocity vectors at the
and the second row, respectively. The left part of each location where the pre-spray is moving, while this is not
image shows a spray tomogram, obtained with the PIV seen in the KIVA-3V simulations. This can be explained
technique described in the previous section. On the right by the fact that the pre-spray is not well predicted by
hand side, the discrete computational parcels used in the KIVA-3V. This is further explained in the next section,
numerical simulations are shown. where droplet sizes are compared.
0
1
2

3
4
5
6
[cm
0.2 ms 0.5 ms 0.8 ms
0
1
2

3
4
5
6
7

8

[cm
1.3 ms 1.8 ms
Figure 8: Comparison of spray tomograms (left) with KIVA-3V computational parcels (right) at various
instants, under ambient pressure (0.1 MPa).

80 80

70 70
60 60
50 50
40 40

30 30

20 20
10 10
(a) 0.8 ms 20 40 60 80
(b) 1.3 ms
80
70
60
50

40

30
20
10 (c) 1.8 ms
20 40 60 80
Figure 9: Comparison of LIF-PIV measured and KIVA-3V predicted velocity vectors at (a) 0.8 ms,
(b) 1.3 ms and (c) 1.8 ms after SOI.
QUANTITATIVE COMPARISON nozzle exit diameter and breakup of the blobs is modeled
using a stability analysis for liquid jets. It seems that this
Figure 10 compares computed and measured tip theory could be appropriate for the physics of the pre-
penetration both for the pre- and the main spray under swirl spray, provided that the stability analysis is valid for
atmospheric conditions. Clearly, at all time instants the the conditions met during the start of DISI injection.
pre-spray penetrates further than the main spray, with the
difference between the two increasing. This trend
correlates with the qualitative observations of the spray Tip Penetration vs. Time
tomograms. As far as the pre-spray is concerned the tip 7
penetration is initially overestimated. This can be
6
attributed to shortcomings in the empirical injection m]
c 5
startup model. At later instances the tip penetration for the n [
pre-spray is underestimated, due to shortcomings in the atio 4
TAB model, as eluded further in Figure 11, where droplet netr 3 Exp. Pre-Spray
e
sizes are compared. On the other hand, the tip p P 2 Exp. Main Spray
penetration of the main spray is consistently Ti KIVA Pre-Spray
1 KIVA Main Spray
overestimated, possibly suggesting a discrepancy on the
0
initial velocity predicted by the liquid sheet breakup model 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
Time after SOI [ms]
or a systematic underestimation of the aerodynamic drag.
Figure 10: Computed and measured tip penetration
profiles for the pre-spray and main spray under ambient
More insight on the behavior of the model can be gained
conditions.
if the calculated SMD is compared to the experimental
measurements at two planes located 27 mm and 36 mm
downstream of the injector, as shown in Figure 11. In
order to ensure the presence of a large enough number SMD vs. Time
of computational parcels at a given plane to produce 100
statistically meaningful SMD results, the sampling was
Exp. - 27 mm
done within planes located – 2 mm of the specified
80 KIVA - 27 mm
location. Inspection of Figure 11 reveals some important
Exp. - 36 mm
features of the pre-spray behavior, compared to the main
spray behavior. While the SMD predictions agree almost m] 60 KIVA - 36 mm
perfectly with measurements for late timings, the droplet mD [
sizes are strongly underestimated for early timings. This M 40
S
can be explained by the fact that for early timings only the
pre-spray has reached the planes of interest. Apparently,
20
modeling of the pre-spray breakup using the TAB model
has significant shortcomings as it results in droplets of
significantly smaller size than the ones measured in the 0
0 0.5 1 1.5 2 2.5 3
experiment. This is consistent with the underestimations in
Time after SOI [ms]
the prediction of tip penetration for the pre-spray, as
described earlier. Note that from the point that the main
spray reaches the measurement location and on, the
Figure 11: Experimental and calculated SMD vs. time at
predicted SMD sizes agree well with the measurements.
27 and 36 mm downstream of the injector.
This is due to the fact that the primary and secondary
atomization models have been calibrated for steady-state
Additional KIVA runs have been performed for injection
conditions, thus being valid for the main spray only. This
under ambient pressure of 0.4 MP. As shown in Figure
suggests that the breakup mechanisms for the pre-spray
12, where the measured and predicted tip penetrations of
and the main spray are different. Hence, further
the pre-spray and main spray are plotted against time,
experimental and numerical investigation is required in
the comparison is not satisfactory. Initially, the
order to determine a suitable model and breakup criteria
penetration of the pre-spray is slightly overestimated, but
for the pre-spray.
as injection proceeds, it is strongly underestimated.
Similarly, the penetration of the main spray is
One possible approach to solve this problem is to
underestimated. Among possible causes for the
calibrate the constants used in the TAB model especially
discrepancies are that (i) the primary atomization model
for this part of the spray. Alternatively, a different model
provides wrong initial conditions (droplet sizes, breakup
can be used for pre-spray break-up. In this case the
length), or (ii) the secondary atomization model breaks up
WAVE model, developed by Reitz [24] could be useful if
parent droplets excessively, or overestimates the
calibrated for these sprays. In this approach, atomization
aerodynamic drag, thus opposing droplet penetration. It
is described by injecting “blobs” with sizes equal to the
must be noted that a direct comparison of SMD cannot be
performed in this case since the spray does not reach penetration for the pre-swirl spray is initially
the specified locations at the correct time. This suggests overestimated and later on underestimated. This
that additional effort needs to be undertaken to implies that the breakup mechanism used for the pre-
understand, model and validate the mechanisms of swirl spray should be improved or replaced.
droplet breakup under higher ambient pressures
• The SMD comparison shows that the prediction for
late timings, when only the main spray is present in
Tip Penetration at P =0.4 MPa
the sampling volume, is very accurate. However, at
6 amb
the start of injection and before the main spray
m] 5 reaches the sampling volume, there is a significant
n [c 4 discrepancy, with the predicted droplets being about
o 60% smaller than the measured ones. This
etrati 3 observation enhances the previous argument about
n the need for enhancing the breakup mechanism for
e 2 Exp. Pre-Spray
P the pre-swirl spray.
Tip 1 KEIxVpA. M Parein-S Spprraayy
0 KIVA Main Spray • Overall, the model compares favorably with data
0 0.5 1 1.5 2
under atmospheric conditions. However,
Time after SOI [ms]
discrepancies occur under higher ambient
pressures, suggesting that the physics of the breakup
Figure 12: Computed and measured tip penetration mechanism should be further investigated for these
profiles for the pre-spray and main spray at P =0.4 conditions.
amb
MPa.

.
ACKNOWLEDGMENTS
CONCLUSIONS
The authors would like to thank the H.H. Rackham School
of Graduate Studies, The University of Michigan, for
A comprehensive model for sprays emerging from high- providing funding for a research visit to Japan in June
pressure swirl injectors in DISI engines has been 2002.
developed accounting for both primary and secondary
atomization. The model considers the transient behavior
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